Difference between revisions of "BIO337 2014"
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* In the news: [http://www.nytimes.com/2013/02/05/science/pigeons-a-darwin-favorite-carry-new-clues-to-evolution.html?src=rechp The pigeon genome] | * In the news: [http://www.nytimes.com/2013/02/05/science/pigeons-a-darwin-favorite-carry-new-clues-to-evolution.html?src=rechp The pigeon genome] | ||
| − | Jan | + | Jan 23, 2014 - Sequence Alignment II |
* [http://www.marcottelab.org/users/CH391L_2013/Files/GALPAS.xls An example of dynamic programming using Excel], created by [http://noble.gs.washington.edu/~mmh1/ Michael Hoffman] (a former CH391L student; you can read more about Michael [http://www.marcottelab.org/users/CH391L_2013/Files/MichaelHoffman.pdf here]) | * [http://www.marcottelab.org/users/CH391L_2013/Files/GALPAS.xls An example of dynamic programming using Excel], created by [http://noble.gs.washington.edu/~mmh1/ Michael Hoffman] (a former CH391L student; you can read more about Michael [http://www.marcottelab.org/users/CH391L_2013/Files/MichaelHoffman.pdf here]) | ||
* [http://www.marcottelab.org/users/CH391L_2013/Files/Lecture5-NBT-primer-dynamicprogramming.pdf Dynamic programming primer] | * [http://www.marcottelab.org/users/CH391L_2013/Files/Lecture5-NBT-primer-dynamicprogramming.pdf Dynamic programming primer] | ||
| − | Jan | + | Jan 21, 2014 - Sequence Alignment I |
* [http://www.marcottelab.org/users/CH391L/CH391L_SeqAlign1.pdf Taejoon's presentation file] | * [http://www.marcottelab.org/users/CH391L/CH391L_SeqAlign1.pdf Taejoon's presentation file] | ||
* [http://www.marcottelab.org/users/CH391L_2013/Files/Lecture4-NBT-primer-BLOSUM.pdf BLOSUM primer] | * [http://www.marcottelab.org/users/CH391L_2013/Files/Lecture4-NBT-primer-BLOSUM.pdf BLOSUM primer] | ||
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* [http://www.marcottelab.org/users/CH391L_2013/Files/BLOSUM62Miscalculations.pdf BLOSUM miscalculations improve performance] | * [http://www.marcottelab.org/users/CH391L_2013/Files/BLOSUM62Miscalculations.pdf BLOSUM miscalculations improve performance] | ||
| − | Jan | + | Jan 16, 2014 - Intro to Python |
| − | + | ||
* [http://www.marcottelab.org/users/CH391L_2013/Files/Lecture3-Python_primer-Spring2013.pdf Python primer] | * [http://www.marcottelab.org/users/CH391L_2013/Files/Lecture3-Python_primer-Spring2013.pdf Python primer] | ||
* [http://www.marcottelab.org/users/CH391L_2013/Files/ProblemSet1_Spring2013.pdf Problem Set 1], due Feb. 5, 2013 | * [http://www.marcottelab.org/users/CH391L_2013/Files/ProblemSet1_Spring2013.pdf Problem Set 1], due Feb. 5, 2013 | ||
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* [http://www.marcottelab.org/users/CH391L_2013/Files/Tvolcanium_genome.txt T. volcanium genome] | * [http://www.marcottelab.org/users/CH391L_2013/Files/Tvolcanium_genome.txt T. volcanium genome] | ||
* 3 mystery genes (for Problem 5): [http://www.marcottelab.org/users/CH391L_2013/Files/Mgene1 Mgene1], [http://www.marcottelab.org/users/CH391L_2013/Files/Mgene2 Mgene2], [http://www.marcottelab.org/users/CH391L_2013/Files/Mgene3 Mgene3] | * 3 mystery genes (for Problem 5): [http://www.marcottelab.org/users/CH391L_2013/Files/Mgene1 Mgene1], [http://www.marcottelab.org/users/CH391L_2013/Files/Mgene2 Mgene2], [http://www.marcottelab.org/users/CH391L_2013/Files/Mgene3 Mgene3] | ||
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| + | Jan 14, 2014 - Introduction | ||
| + | * Some warm-up videos to get you started on Python: [http://www.codecademy.com/tracks/python Python coding for beginners]<br> | ||
| + | * We'll be conducting homework using the online environment [http://rosalind.info/faq/ Rosalind]. Go ahead and register on the site. | ||
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== Syllabus & course outline == | == Syllabus & course outline == | ||
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Some online references:<br> | Some online references:<br> | ||
[http://lectures.molgen.mpg.de/ An online bioinformatics course]<br> | [http://lectures.molgen.mpg.de/ An online bioinformatics course]<br> | ||
| − | Assorted bioinformatics resources on the web: [http://zlab.bu.edu/zlab/links.shtml | + | Assorted bioinformatics resources on the web: [http://zlab.bu.edu/zlab/links.shtml Assorted links]<br> |
| − | + | ||
[http://onlamp.com/lpt/a/2727 Beginning Python for Bioinformatics]<br> | [http://onlamp.com/lpt/a/2727 Beginning Python for Bioinformatics]<br> | ||
Online probability texts: [http://omega.albany.edu:8008/JaynesBook.html #1], [http://www-users.york.ac.uk/~mb55/pubs/pbstnote.htm #2], [http://www.dartmouth.edu/~chance/teaching_aids/books_articles/probability_book/pdf.html #3]<br> | Online probability texts: [http://omega.albany.edu:8008/JaynesBook.html #1], [http://www-users.york.ac.uk/~mb55/pubs/pbstnote.htm #2], [http://www.dartmouth.edu/~chance/teaching_aids/books_articles/probability_book/pdf.html #3]<br> | ||
Revision as of 23:45, 10 January 2014
BIO337 Systems Biology/Bioinformatics
Course unique #: 50524
Lectures: Tues/Thurs 11 – 12:30 PM in BUR 212
Instructor: Edward Marcotte, marcotte@icmb.utexas.edu
- Office hours: Wed 11 AM – 12 noon in MBB 3.148BA Phone: 512-471-5435
TA: Dakota Derryberry, dakotaz@utexas.edu
- TA Office hours: Mon 4 - 5 PM/Fri 9 – 10 AM in MBB 3.304 Phone: 512-232-2459
Lectures & Handouts
Jan 14, 2014 - Introduction
- Some warm-up videos to get you started on Python: Python coding for beginners
- We'll be conducting homework using the online environment Rosalind. Go ahead and register on the site.
Syllabus & course outline
An introduction to systems biology and bioinformatics, emphasizing quantitative analysis of high-throughput biological data, and covering typical data, data analysis, and computer algorithms. Topics will include introductory probability and statistics, basics of Python programming, protein and nucleic acid sequence analysis, genome sequencing and assembly, proteomics, synthetic biology, analysis of large-scale gene expression data, data clustering, biological pattern recognition, and gene and protein networks.
Open to upper division undergraduates in natural sciences and engineering.
Prerequisites: Biochem I or equivalent (e.g. CH339J or CH339K/L), basic familiarity with molecular biology.
Note that this is not a course on practical sequence analysis or using web-based tools. Although we will use a number of these to help illustrate points, the focus of the course will be on learning the underlying algorithms and exploratory data analyses and their applications, esp. in high-throughput biology.
Most of the lectures will be from research articles and slides posted online, with some material from the...
Optional text (for sequence analysis): Biological sequence analysis, by R. Durbin, S. Eddy, A. Krogh, G. Mitchison (Cambridge University Press),
For biologists rusty on their stats, The Cartoon Guide to Statistics (Gonick/Smith) is very good.
Some online references:
An online bioinformatics course
Assorted bioinformatics resources on the web: Assorted links
Beginning Python for Bioinformatics
Online probability texts: #1, #2, #3
No exams will be given. Grades will be based on online homework (counting 30% of the grade), 3 problem sets (given every 2-3 weeks and counting 15% each towards the final grade) and a course project (25% of final grade), which will be collaborative. Cross-discipline collaborations will be encouraged. The course project will consist of a research project on a bioinformatics topic chosen by the students (with approval by the instructor) containing an element of independent computational biology research (e.g. calculation, programming, database analysis, etc.). This will be turned in as a link to a web page.
Online homework will be assigned and evaluated using the free bioinformatics web resource Rosalind.
The final project is due by midnight April 28, 2014.
- How to make a web site for the final project
